phalanx
Searx
phalanx | Searx | |
---|---|---|
13 | 154 | |
341 | 13,152 | |
- | - | |
0.0 | 7.7 | |
about 1 year ago | 8 months ago | |
Go | Python | |
Apache License 2.0 | GNU Affero General Public License v3.0 |
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phalanx
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An alternative to Elasticsearch that runs on a few MBs of RAM
Somewhat related, this guy: https://github.com/mosuka/ seems to be very passionate about search service.
He built two distributed search services:
- https://github.com/mosuka/phalanx, written in Go.
- https://github.com/mosuka/bayard, written in Rust.
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What is the coolest Go open source projects you have seen?
Don’t forget about Phalanx if you like Bleve/Bluge.
- Cloud-native distributed search engine written in Go
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I want to dive into how to make search engines
I've never worked on a project that encompasses as many computer science algorithms as a search engine. There are a lot of topics you can lookup in "Information Storage and Retrieval":
- Tries (patricia, radix, etc...)
- Trees (b-trees, b+trees, merkle trees, log-structured merge-tree, etc..)
- Consensus (raft, paxos, etc..)
- Block storage (disk block size optimizations, mmap files, delta storage, etc..)
- Probabilistic filters (hyperloloog, bloom filters, etc...)
- Binary Search (sstables, sorted inverted indexes, roaring bitmaps)
- Ranking (pagerank, tf/idf, bm25, etc...)
- NLP (stemming, POS tagging, subject identification, sentiment analysis etc...)
- HTML (document parsing/lexing)
- Images (exif extraction, removal, resizing / proxying, etc...)
- Queues (SQS, NATS, Apollo, etc...)
- Clustering (k-means, density, hierarchical, gaussian distributions, etc...)
- Rate limiting (leaky bucket, windowed, etc...)
- Compression
- Applied linear algebra
- Text processing (unicode-normalization, slugify, sanitation, lossless and lossy hashing like metaphone and document fingerprinting)
- etc...
I'm sure there is plenty more I've missed. There are lots of generic structures involved like hashes, linked-lists, skip-lists, heaps and priority queues and this is just to get 2000's level basic tech.
- https://github.com/quickwit-oss/tantivy
- https://github.com/valeriansaliou/sonic
- https://github.com/mosuka/phalanx
- https://github.com/meilisearch/MeiliSearch
- https://github.com/blevesearch/bleve
- https://github.com/thomasjungblut/go-sstables
A lot of people new to this space mistakenly think you can just throw elastic search or postgres fulltext search in front of terabytes of records and have something decent. The problem is that search with good rankings often requires custom storage so calculations can be sharded among multiple nodes and you can do layered ranking without passing huge blobs of results between systems.
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Why Writing Your Own Search Engine Is Hard (2004)
For those curious, I'm on my 3rd search engine as I keep discovering new methods of compactly and efficiently processing and querying results.
There isn't a one-size-fits all approach, but I've never worked on a project that encompasses as many computer science algorithms as a search engine.
- Tries (patricia, radix, etc...)
- Trees (b-trees, b+trees, merkle trees, log-structured merge-tree, etc..)
- Consensus (raft, paxos, etc..)
- Block storage (disk block size optimizations, mmap files, delta storage, etc..)
- Probabilistic filters (hyperloloog, bloom filters, etc...)
- Binary Search (sstables, sorted inverted indexes)
- Ranking (pagerank, tf/idf, bm25, etc...)
- NLP (stemming, POS tagging, subject identification, etc...)
- HTML (document parsing/lexing)
- Images (exif extraction, removal, resizing / proxying, etc...)
- Queues (SQS, NATS, Apollo, etc...)
- Clustering (k-means, density, hierarchical, gaussian distributions, etc...)
- Rate limiting (leaky bucket, windowed, etc...)
- text processing (unicode-normalization, slugify, sanitation, lossless and lossy hashing like metaphone and document fingerprinting)
- etc...
I'm sure there is plenty more I've missed. There are lots of generic structures involved like hashes, linked-lists, skip-lists, heaps and priority queues and this is just to get 2000's level basic tech.
- https://github.com/quickwit-oss/tantivy
- https://github.com/valeriansaliou/sonic
- https://github.com/mosuka/phalanx
- https://github.com/meilisearch/MeiliSearch
- https://github.com/blevesearch/bleve
A lot of people new to this space mistakenly think you can just throw elastic search or postgres fulltext search in front of terabytes of records and have something decent. That might work for something small like a curated collection of a few hundred sites.
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Show HN: I built a self hosted recommendation feed to escape Google's algorithm
Is there a tool that automatically forwards every URL + HTML of the page you visit to a webhook so you could write an endpoint that would index everything?
If not, I would love to see this add a "forward to webhook" option. I would be happy to write up a real backend that parsed the content and indexed it.
Actually, there are lots of OS projects for this: https://github.com/quickwit-oss/tantivy, https://github.com/valeriansaliou/sonic, https://github.com/mosuka/phalanx, https://github.com/meilisearch/MeiliSearch, etc...
- Phalanx is a cloud-native distributed search engine with REST API written in Go
- Phalanx v0.3.0, a distributed search engine written in Go, has been released
- Phalanx 0.2.0, a distributed search engine written in Go, has been released
- Phalanx - A cloud-native full-text search and indexing server written in Go built on top of Bluge
Searx
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Challenging projects every programmer should try
I think searx was largely built by a single person.
https://github.com/searx/searx
- Searx is no longer maintained
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I want to organize my few TBs of data in a nice way
I use Recoll to index all of it. Recoll WebUI exposes an API, which I plugged into Searx.
- Now you can search on Google for free: Solution with API
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Google Removes Sort by Date options in search
The quality of Google search results has been awful for many years now, but if you still want to use it, the only usable way is via a frontend like Searx[1]. Using any of Google's frontends for any of their services is an exercise in frustration from dodging ads and fighting their hostile UI.
[1]: https://github.com/searx/searx
- Ask HN: Best search engine alternatives to Google?
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Any way to create RSS of google?
RSS-Bridge has a Google search adapter. You can also fake it with Searx (which offers RSS feeds of search results).
- How is everyone doing with most of reddit gone?
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Local self ask
I've recently wondered how effective local models were at chaining together thoughts as proposed in https://ofir.io/self-ask.pdf. Turns out they are indeed capable of doing so while also creating reasonable chains of thoughts that are easily as good as OpenAI's models. To make it completely free to run I used SearX running inside a Docker container with a second model curating the search results for the main model to get answers from the web.
What are some alternatives?
tantivy - Tantivy is a full-text search engine library inspired by Apache Lucene and written in Rust
searxng - SearXNG is a free internet metasearch engine which aggregates results from various search services and databases. Users are neither tracked nor profiled.
ipfs-search - Search engine for the Interplanetary Filesystem.
Yacy - Distributed Peer-to-Peer Web Search Engine and Intranet Search Appliance
MeiliSearch - A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
whoogle-search - A self-hosted, ad-free, privacy-respecting metasearch engine
markov - Materials for book: "Markov Chains for programmers"
go-sstables - Go library for protobuf compatible sstables, a skiplist, a recordio format and other database building blocks like a write-ahead log. Ships now with an embedded key-value store.
duckduckgo-locales - Translation files for <a href="https://duckduckgo.com"> </a>
search-engines - Reviewing alternative search engines
searxng - SearXNG is a free internet metasearch engine which aggregates results from various search services and databases. Users are neither tracked nor profiled. This is a fork of SearXNG used by searx.tiekoetter.com